How to extract social media handles and hashtags
Start with pasted post text or a local text file. After you choose an extraction mode, Output text lists the handles and hashtags it found. Unique only changes repeated lines in Output text, while Frequency Count groups the matches and shows how often each group occurs.
Extract @mentions or #hashtags from text
- Paste your caption, thread, or other text into the input area, or select Upload and choose a text file.
- Select Both, @Mentions only, or #Hashtags only.
- Keep Unique only selected to show one line per token, or clear it to keep repeated matches.
- Enable Case sensitive to separate tokens that differ only by capitalization, then check Output text and Frequency Count.
- Select Copy or Download to take the displayed list to another document.
What the extractor matches
The Social Media Handle & Hashtag Extractor looks for @ or # followed by one or more letters, numbers, or underscores. A token must begin at the start of the text or after a character that is not a letter, number, or underscore. Punctuation ends the token.
Input: Love this collab with @nike and @adidas #running #fitness #fitness
Output with Both and Unique only:
-- @Mentions --
@adidas
@nike
-- #Hashtags --
#fitness
#runningFor example, #fitness! contributes #fitness. In email@nike, the @ follows a letter, so the pattern skips it. Unicode letters and numbers are included alongside underscores.
What Unique only and Case sensitive change
Unique only changes Output text. When it is selected, repeated tokens appear once. Clear it and each matching occurrence gets its own line. Frequency Count still groups all matches and counts every occurrence after the selected mode and case setting are applied.
Case sensitive controls grouping. With it unchecked, #Marketing and #marketing share a count, and the first spelling is shown. Enable it to keep those spellings separate. Frequency Count sorts rows by count, then uses alphabetical order when counts tie.
When Both is selected, a group with matches gets a heading in Output text: -- @Mentions -- for mentions or -- #Hashtags -- for hashtags. The result area reports the number of displayed results. Copy and Download remain unavailable while the output has no lines.
For a batch of captions, leave Unique only selected when the review needs one line per token, then use Frequency Count to see repeated tags. Select @Mentions only to collect account references, or choose #Hashtags only before copying the list into another document.
Keep Case sensitive selected when capitalization needs to remain visible in separate rows. Clear it when #Marketing and #marketing should share one count.
When another text extractor fits better
Use Text Parsing & Data Extraction to choose among text-matching jobs. This extractor handles @mentions and #hashtags. Custom Regex Extractor handles a pattern you define, Extract Lines Containing a String keeps complete matching lines, and Extract URLs from Text targets URLs.
Frequently asked questions
How do I extract social media handles and hashtags from text?
Paste the text, choose Both, @Mentions only, or #Hashtags only, and read the matches in Output text. Then adjust Unique only or Case sensitive to change the displayed grouping.
Can I extract only hashtags or only mentions?
Choose #Hashtags only for hashtag tokens or @Mentions only for handles. Both keeps the two groups in Output text, with a heading for each group that has matches.
How does Frequency Count count repeated hashtags?
Frequency Count counts matching occurrences after the selected mode and case setting are applied. It counts repeats even when Unique only is selected, because that checkbox changes Output text.
What file types can I upload for hashtag extraction?
Upload lists .txt, .csv, .log, and .md extensions, along with text/plain. After the file is loaded, its text is placed in the input area for extraction.
Why did the extractor skip a handle in an email address?
The extractor requires @ or # to start after the text begins or after a character that is not a letter, number, or underscore. In email@nike, the @ follows a letter, so the pattern skips it.